Your Gateway to Generative AI and Beyond
-
🎓 Concepts & Fundamentals
Dive into core topics like Transformers, Diffusion Models, Vector Embeddings, RAG, and more. -
🛠️ Hands-on Projects
Jupyter notebooks, prototypes, and real-world GenAI use cases. -
📚 Learning Resources
Curated lists of must-read papers, tutorials, and tools to level up your AI game. -
🧩 Components & Architectures
Breakdown of modern GenAI systems: LLMs, prompt engineering, vector databases, orchestration layers, etc. -
🌐 Explainers for Everyone
Simple and intuitive explanations aimed at making GenAI accessible to all.
Because context is everything. In the GenAI era, understanding how models use and generate context is key to building smarter, safer, and more capable systems. This repo is your guide to mastering that.
| Topic | Description |
|---|---|
RAG-Explained.ipynb |
Step-by-step intro to Retrieval-Augmented Generation |
vector-databases.md |
Guide to choosing the right vector DB for your project |
prompt-engineering/ |
(Coming soon) Prompting strategies, templates & hacks |
open-source-llms.md |
(Coming soon) Explore powerful open-source LLMs |
📌 Coming Soon – Stay tuned for exciting updates:
- LangChain & LlamaIndex walkthroughs
- Multi-modal GenAI examples
- Agent-based systems
- Real-time GenAI app demos
This is a living project — contributions, questions, and feedback are all welcome!
- ⭐ Star the repo if you find it helpful
- 🧵 Open an issue or discussion to share ideas
- 🔧 PRs are more than welcome
Let’s connect and grow together in the GenAI space:
- 🐦 Twitter (X)
- ✍️ Medium